Erik Olsson
Papers
8
Total Citations
152
H-Index
5
About
Erik Olsson is a researcher whose work sits at the intersection of artificial intelligence, industrial automation, and intelligent maintenance systems. His primary contributions center on applying case-based reasoning (CBR) to fault diagnosis and condition monitoring in complex industrial environments, with a particular focus on robots, manufacturing equipment, and sensor-driven diagnostics. Olsson's most influential work, "Fault Diagnosis in Industry Using Sensor Readings and Case-Based Reasoning" (2004), has garnered 67 citations and established foundational approaches for using AI-driven experience reuse to improve the speed and reliability of industrial fault detection. His companion study applying CBR to acoustic signal analysis in industrial robots (35 citations) further demonstrated how sound and sensor data could be intelligently interpreted to identify mechanical failures. Together, these papers positioned Olsson as a pioneering voice in AI-enhanced predictive maintenance. Beyond diagnostics, Olsson extended his research into agent-based monitoring systems and decision-support frameworks, exploring how autonomous agents can assist human operators in real-time industrial settings. His work on mobile production modules and the Factory-in-a-Box concept reflects a broader vision for flexible, reconfigurable manufacturing. With over 150 cumulative citations, Olsson's research continues to inform both industrial practitioners and AI researchers seeking smarter, more adaptive maintenance solutions.
Research Focus
Key Achievements
Top Papers
- 1Fault diagnosis in industry using sensor readings and case-based reasoning67 citations · 2004
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- 4Case-Based Reasoning for Medical and Industrial Decision Support Systems18 citations · 2010
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